Adaptive Hybrid Tracking Algorithms for Radio Signal Parameters Estimations

ABSTRACT

A digital direct line-of-sight (DLOS) intermediate frequency (IF) signal of a DLOS component of an RF carrier signal transmitted by a transmitter located above the surface of the earth and a digital reflected IF signal of a reflected component of the carrier signal that is reflected from a specular point (SP) on the surface of the earth are received. Modeled reference signal parameters are generated using the digital DLOS IF signal and known locations of one or more receiving antennas, the transmitter, and the SP. A reference signal is generated based on the modeled reference signal parameters and feedback of a previously estimated Δϕ. The reference signal is correlated with the digital reflected IF signal to produce in-phase (I) and quadrature-phase (Q) correlation results. An estimated C/N0 and an estimated Δϕ for the digital reflected IF signal are calculated from the correlation results.

RELATED APPLICATIONS

This application is a continuation application of U.S. patentapplication Ser. No. 17/141,450, filed Jan. 5, 2021, which claims thebenefit of U.S. Provisional Patent Application Ser. No. 62/963,713,filed on Jan. 21, 2020, the content of all of which is incorporated byreference herein in their entireties.

GOVERNMENT INTEREST

This invention was made with government support under grant numberNNX15AT54G awarded by NASA. The government has certain rights in theinvention.

TECHNICAL FIELD

The teachings herein relate to operating a receiver to estimateparameters of a radio frequency (RF) carrier signal reflected from theearth's surface in order to measure topographical features on theearth's surface. More particularly, the teachings herein relate tosystems and methods for estimating the carrier-to-noise ratio (C/N₀) andphase correction (Δϕ) of a reflected RF carrier signal. The systems andmethods disclosed herein can be performed in conjunction with aprocessor, controller, microcontroller, or computer system, such as thecomputer system of FIG. 1 .

BACKGROUND

Remote sensing is used to measure topographical features on the earth'ssurface. Remote sensing satellite and airborne devices havetraditionally been used to measure topographical features with heightson the order of kilometers (km) and even meters (m) because they canprovide global coverage. However, for topographical features withheights on the order of centimeters (cm), additional devices inconjunction with satellite and airborne devices have traditionally beenused. For example, geodetic global navigation satellite system (GNSS)receivers on buoys in conjunction with the GNSS satellites have beenused to measure centimetric sea surface wave heights. Unfortunately,however, additional devices, such as receivers on buoys, can onlyprovide point-wise measurements.

As a result, systems and methods have been developed to improve themeasurement capability of remote sensing satellite and airborne devices.For example, satellite and airborne GNSS receivers are designed tocalculate a pseudorange based on the parameters (information) in thereceived GNSS signal. However, the calculated pseudorange can onlyprovide height measurements on the order of tens of meters or, at best,on the order of meters. Consequently, the pseudorange cannot be used toprovide centimetric height measurements.

GNSS and other types of navigation or communication satellite orairborne systems, however, also include a carrier signal. Calculatingthe phase of the carrier signal of such systems can be used to determineheight measurements on the order of centimeters. In other words, carrierradio signals transmitted from satellites or other airborne platforms,though designed for navigation or communication purposes, can be used tosense signal propagation environments with a resolution on the order ofcentimeters. This is because the carrier signals contain informationabout the properties of the signal propagation medium. Some commonlyused signals include GNSS signals (such as GPS, GLONASS, Galileo, andBeidou, etc.) and communication satellite signals.

Global navigation satellite system reflectometry (GNSS-R) is one suchremote sensing application where GNSS carrier signals reflected from theearth's surface such as ocean and land cover are used to derive theproperties of the reflection surface. For example, reflections fromocean surface can be used to derive ocean wind speed, roughness, waveheights, sea ice thickness, salinity, and sea-level changes; reflectionsfrom land cover can be used to infer soil moisture,snow-water-equivalent (SWE), and vegetation states.

FIG. 2 is an exemplary diagram 200 showing components of a GNSS-Rsystem, upon which embodiments of the present teachings may beimplemented. Direct line-of-sight (DLOS) GNSS signals and reflected GNSSsignals from earth surface 201 are received by a GNSS-R receiver mountedon low earth orbit (LEO) satellite platform 220. The reflected GNSSsignal may contain valuable information about the reflection surface,and, in the meanwhile, the reflection surface may have a significantimpact on the signal characteristics. For example, the GNSS signalreflected over the ocean surface may contain information about the oceansurface height. If the ocean surface is relatively calm, the reflectedGNSS signals over it tend to be coherent, and it would be possible toobtain high-precision (centimeter-level) observations of the oceansurface height.

Signal transmitters 210, 211, 212, 213, and 214 represent the GNSSsatellites. The receiver of LEO satellite-based GNSS-R receiver platform220 includes, for example, two antennas to receive the DLOS signal andthe reflected signal, respectively. GNSS signals 230, 231, 232, 233, and234 travel directly from the GNSS satellite transmitters 210, 211, 212,213, and 214, respectively, to LEO satellite-based GNSS-R receiverplatform 220. GNSS signal 230A, for example, travels from the GNSSsatellite transmitter 210 to ocean surface 202 on earth 201. GNSS signal230B results from GNSS signal 230A after being reflected by oceansurface 202 at point 240. GNSS signal 230B travels from ocean surface202 to LEO satellite-based GNSS-R receiver platform 220. Specular point(SP) 240 represents the location where GNSS signal 230A is reflected.

The current operational GNSSs include the global positioning system(GPS), the Galileo navigation system, the global navigation satellitesystem (GLONASS), the BeiDou navigation satellite system, and otherregional satellite navigation systems. Signal transmitters 210, 211,212, 213, and 214 are designed to broadcast radio signals at certainfrequencies. For example, current operational GPS satellites broadcastthree civil signals simultaneously, i.e., L1C/A, L2C, and L5, at 1575.42MHz, 1227.6 MHz, and 1176.45 MHz bands, respectively.

The receiver of platform 220 usually has two or more antennas, azenith-looking antenna to receive the DLOS GNSS signals 230, 231, 232,233, and 234 and one or several nadir-looking or horizontal-lookingantennas to receive GNSS signal 230B and other reflected signals fromearth 201.

The receiver of platform 220 processes GNSS signals usually at two ormore frequencies, for example, GPS L1 and L2. This means the GNSSsignals 230, 230A, 230B, 231, 232, 233, and 234 contain signalcomponents at two or more frequencies. The DLOS signals 230, 231, 232,233, and 234 are used for the precise orbit determination (POD) of LEOsatellite-based platform 220.

Coherent reflection occurs when the reflection surface is smooth. If theroughness of the reflection surface is comparable to or larger than asignal wavelength, the reflection is noncoherent. Unfortunately,reflections from an ocean surface, such as surface 202, often containvery little coherent signal components, because the ocean surface isrelatively rough and the GNSS carrier wavelengths are in the order of afew 10s of centimeters. Much of the current state-of-the-arttechnologies work with noncoherent reflections. It is, however, thecoherent signal component that enables accurate range measurementretrieval (cm-level) and high spatial and temporal resolution.

FIG. 3 is an exemplary diagram 300 showing coherent and noncoherentreflections of carrier signals from smooth and rough surfacesrespectively to a receiver, upon which embodiments of the presentteachings may be implemented. GNSS signals 310 are transmitted by one ormore GNSS satellite transmitters (not shown) and are reflected by smoothsurface 301 or rough surface 302 towards LEO satellite-based GNSS-Rreceiver platform 320. Smooth surface 301 produces coherent reflectedsignals 311, and rough surface 302 produces noncoherent reflectedsignals 312, for example. LEO satellite-based GNSS-R receiver platform320 also receives DLOS signals 313 from the one or more GNSS satellitetransmitters.

The low signal-to-noise ratio (SNR) and the large signal amplitudefluctuations caused by multipath interferences in the ocean reflectedcoherent signal impose great challenges in the receiver carrier signalprocessing. In addition, the carrier signal is transmitted by satellitesor airborne devices moving at enormous speeds. As a result, carriersignal processing is also affected by frequency shifting due to theDoppler effect. In other words, in order to obtain centimetric heightmeasurements from coherent carrier signal processing, a receiver mustovercome challenges imposed by low signal SNR, large signal amplitudefluctuations, and signal frequency shifts due to the Doppler effect.

At least two methods of carrier signal processing were previouslydeveloped to account for low signal SNR, large signal amplitudefluctuations, and signal frequency shifts due to the Doppler effect.Both of these methods are performed by an RF receiver during the carriertracking portion of intermediate frequency (IF) signal processing.

FIG. 4 is an exemplary block diagram 400 of a GNSS-R receiver showingthe location of IF signal processing, upon which embodiments of thepresent teachings may be implemented. Antenna system 401 represents amulti-frequency antenna adapted to signal frequencies, such as GPS L1and L2, with right-hand circular polarization (RHCP). Antenna system 402represents a multi-frequency antenna adapted to signal frequencies, suchas GPS L1 and L2, with left-hand circular polarization (LHCP). Antennasystem 402 may also be a phased array antenna.

RF front-end 410 is configured to perform signal conditioning anddown-conversions, where the signal spectrum is moved from RF to an IF ora baseband frequency. RF front-end 410 may include one or more signaldown-converters (not shown) that can be configured to multiple frequencysignals driven by a common local oscillator (not shown). The analogmulti-frequency outputs from RF front-end 410 can be digitized andquantized in analog-to-digital converter (ADC) 420.

The output from ADC 420, i.e., the digitalized IF or baseband signals,is input to IF signal processing system 430, which is used to estimatethe signal parameters of the input IF signal, decode the navigation databits, and obtain receiver position, velocity, and time (PVT) solutions.

The output from IF signal processing system 430, i.e., signal parameterestimations of both DLOS and reflected signals, the PVT of the receiverplatform, and the orbit parameters of the transmitter platform is inputto the scientific parameters retrieval module 440.

Scientific parameters retrieval module 440 is used to retrievescientific parameters, such as water level height, soil moisture, etc.

FIG. 5 is an exemplary block diagram 500 showing the IF signalprocessing in a GNSS-R receiver used to account for low signal SNR,large signal amplitude fluctuations, and signal frequency shifts due tothe Doppler effect, upon which embodiments of the present teachings maybe implemented. The IF signal processing in FIG. 5 includes threeseparate functions. These are direct or DLOS signal processing 510,reflected signal code phase delay and Doppler frequency modeling 520,and reflected signal processing 530.

In DLOS signal processing function 510, GNSS software receiver 512receives DLOS GNSS signals 511, processes DLOS GNSS signals 511 usingphase-lock loops (PLL) for carrier tracking and delay-lock loops (DLL)for code phase tracking, and generates parameters 513, including PVTparameters for the LEO satellite-based receiver platform, signalparameters of DLOS GNSS signals 511 (i.e., code delay, Dopplerfrequency, carrier phase), and decoded navigation bits, etc.

In reflected signal code phase and Doppler frequency modeling function520, models 522 of the code delay and Doppler frequency of the reflectedsignal are created. Models 522 are created based on an estimatedposition 521 of the SP. A minimum path length method is used to estimatethe SP position by minimizing the reflected path length whileconstraining the SP to the earth's surface. The earth's surface ismodeled with a WGS84 ellipsoid or a mean sea surface (MSS) model, forexample.

In reflected signal processing function 530, code tracking 531 andcarrier tracking 532 are performed. In code tracking 531, pseudorandomnoise codes (PRN) are shifted in the time domain and correlated withreflected signal 533 to produce code delay estimates. Based on the codedelay estimates, range observation 534 is obtained (with precision inmeters or tens of meters) and applied for altimetry-related GNSS-Rapplications.

In carrier tracking 532, the objective is to measure parameters 535 (thetotal carrier phase and the amplitude or C/N₀) of received reflectedsignal 533. With the carrier phase measurement, range observation at thecentimeter level can be obtained. However, as described above, carriertracking 532 is sensitive to low C/N₀ and rapid phase changes. Inaddition, received reflected signal 533 is often adversely affected bymultipath scattering and the degradation from the earth's surfacereflection.

One method of carrier tracking developed to account for low signal C/N₀,large signal amplitude fluctuations, and signal frequency shifts due tothe Doppler effect is called master-slave open-loop (MS-OL) processing.In MS-OL processing, a carrier signal replica for the reflected signalis generated based on a Doppler model, which is based on the GNSSsatellite orbit, receiver platform PVT solution, and the DLOS trackingresults. The carrier signal replica is then correlated with thereflected GNSS signal.

FIG. 6 is an exemplary block diagram 600 showing MS-OL carrier trackingprocessing, upon which embodiments of the present teachings may beimplemented. In FIG. 6 , generator 610 generates a carrier signalreplica based on Doppler model 522. Doppler model 522 is created inreflected signal code phase and Doppler frequency modeling function 520of FIG. 5 , for example.

Returning to FIG. 6 , correlator function 620 correlates the carriersignal replica with reflected GNSS signal 630. In-phase (I) andquadrature (Q) correlation outputs are obtained from the correlation.C/N0 640 of reflected GNSS signal 630 is estimated from the I and Qcorrelation outputs based on a power ratio method or a signalintensity-based approach, for example.

Discriminator function 650 applies a four-quadrant discriminator to theI and Q correlation outputs to produce a Δϕ. The Δϕ is used by phasecorrection function 660 to produce phase range measurement 670, whichcan be defined as the carrier phase multiplied by the carrierwavelength. Phase range measurement 670 is used to calculate acentimetric ocean surface height, for example.

The MS-OL carrier tracking method, as shown in FIG. 6 , is simple toimplement and has excellent robustness. However, it does not have afilter in the tracking loop. As a result, when C/N₀ 640 is low or whenreflected carrier signal 630 experiences multipath interferences, theMS-OL tracking results can be noisy, and the errors produced bydiscriminator function 650 can accumulate in the carrier phaseobservation and cause numerous phase discontinuities.

FIG. 7 is an exemplary plot 700 of the C/N₀ and the Δϕ of a reflectedGNSS carrier signal estimated using MS-OL carrier tracking processing,upon which embodiments of the present teachings may be implemented. Inplot 700, estimated data values C/N₀ and Δϕ are plotted as a function oftime. The time values represent different specular points on the surfaceof the earth from which a reflected component of the RF carrier signalwas analyzed. FIG. 7 shows that, when C/N₀ spikes lower, MS-OL trackingcan produce discontinuities in Δϕ. For example, at time 710, the largedecrease in C/N₀ causes a discontinuity in Δϕ.

In order to overcome the noisy tracking results produced by MS-OLcarrier tracking processing, another method of carrier tracking calledadaptive closed-loop (ACL) processing was developed. When properlytuned, ACL processing provides improved accuracy and fewer phasediscontinuities in carrier phase measurements as compared to MS-OLprocessing or the conventional closed-loop PLL processing.

FIG. 8 is an exemplary block diagram 800 showing ACL carrier trackingprocessing, upon which embodiments of the present teachings may beimplemented. FIG. 8 shows that ACL processing has two main differencesfrom the MS-OL processing shown in FIG. 6 . First, ACL processing doesnot rely on a Doppler model. Instead, the reference signal is generatedbased on the feedback from a previously estimated carrier phase andDoppler frequency 880. Second, the carrier tracking problem isreformulated into a closed-loop feedback control problem. Coding andcarrier generator 810 obtains an estimation of a state vector based onsignal dynamics and measurement instead of a simple phase correction, asis done in MS-OL processing.

In particular, coding and carrier generator 810 generates local carrierreplicas using the predicted state vector. The state vector consists ofa carrier phase, Doppler frequency, and Doppler frequency rate.

As in MS-OL processing, correlator function 820 correlates the carriersignal replicas with reflected GNSS signal 830. In-phase (I) andquadrature (Q) correlation outputs are obtained from the correlation.Again, C/N₀ 840 of reflected GNSS signal 830 can be estimated from the Iand Q correlation outputs based on a power ratio method or a signalintensity-based approach, for example.

Discriminator function 850 applies a four-quadrant discriminator to theI and Q correlation outputs to produce a Δϕ. The Δϕ is used by estimatorfunction 860 to produce phase range and Doppler frequency estimates 880.

The state vector used by coding and carrier generator 810 is estimatedusing a standard Kalman filter (KF), for example. The use of a KF makesACL processing highly dependent on tuning the KF. For example, in tuningthe KF, process noise covariance matrices must be selected and noisevariance must be measured. The noise covariance matrices are selectedbased on empirical phase noise model 870 and the noise variance ismeasured based on C/N₀ 840, for example.

The ACL carrier tracking method, as shown in FIG. 8 , provides improvedresults by taking advantage of the characteristics of signal dynamicsand adaptive filter tuning based on a real-time estimated C/N₀. However,one problem with using ACL processing for GNSS-R signal tracking is thatits performance is dependent on accurate initialization and tuning ofthe filter. ACL processing can lose lock of the reflected signal whenthere is not a sufficient amount of coherent signal. The amount ofcoherent reflection varies with the elevation angle, the reflectionsurface conditions, etc. Therefore, a strong coherent component does notconsistently exist in the GNSS-R signal. As a result, ACL processing hastraditionally been used for postprocessing data. In other words, ACLprocessing has traditionally been impractical for onboard operation inreal-time.

In summary, MS-OL carrier tracking processing is simple and robust.However, when C/N₀ is low or when the reflected carrier signalexperiences multipath interferences, the MS-OL tracking results can benoisy, and the errors produced can accumulate in the carrier phaseobservation and cause numerous phase discontinuities. ACL carriertracking processing provides improved results by taking advantage of thecharacteristics of signal dynamics and adaptive filter tuning based on areal-time estimated C/N₀. However, ACL processing can lose lock of thereflected signal when there is not a sufficient amount of coherentsignal.

As a result, additional systems and methods are needed to provide signaltracking of reflected carrier signals without phase discontinuities andwithout losing lock of the reflected signals.

SUMMARY

Various embodiments disclosed herein relate to systems, methods, andtechniques for tracking coherent reflection signals received ondifferent types of dynamic platforms.

The radio receiver can be mounted on a low earth orbit (LEO) satellite,an airborne, or a ground-based platform, etc. The receiver systemincludes one antenna to receive the DLOS signals and one or more otherantenna(s) to receive the reflected signals from the earth's surface buttransmitted from the same radio source. In some circumstances, both DLOSsignals from the source and reflected signals from the earth's surfacecan be received by a single antenna. The received signals reflected fromthe earth's surface, such as ocean and land, are used to derive theproperties of the reflection surface, such as water level height, seaice thickness, soil moisture, etc. For signals of coherent reflections,various embodiments can implement a signal tracking procedure and obtainhigh-precision, high-resolution carrier phase-based range measurements.

In various embodiments, systems and methods for adaptive hybrid tracking(AHT) are used to estimate the carrier signal parameters, i.e., Dopplerfrequency and carrier phase, of the reflected radio signal received bythe receiver after being down-converted to an IF and digitalized. Insome embodiments, systems and methods for AHT formulate a feedback loopand an estimation problem. These systems and methods utilize estimatedsignal parameters, such as the modulation code phase and Dopplerfrequency, of the DLOS signal, the specular reflection model, and thecarrier phase feedback to generate the local reference signal. Thesesystems and methods adopt an estimator to estimate the carrier signalparameters of reflected radio signal based on the signal dynamics model,the carrier phase error measurement, and the measurement model.

In some embodiments, the code tracking of the reflected signal isimplemented as open-loop (OL) tracking. Typical platforms are equippedwith sensors and capabilities such as a navigation processor that mayuse the DLOS signals to determine the receiver platform PVT.

While multiple embodiments are disclosed, still other embodiments of thepresent technology will become apparent to those skilled in the art fromthe following detailed description, which shows and describesillustrative embodiments of the technology. As will be realized, thetechnology is capable of modifications in various aspects, all withoutdeparting from the scope of the present technology. Accordingly, thedrawings and detailed description are to be regarded as illustrative innature and not restrictive.

The phrases “in various embodiments,” “in some embodiments,” “accordingto some embodiments,” “in the embodiments shown,” “in otherembodiments,” and the like generally mean the particular feature,structure, or characteristic following the phrase is included in atleast one implementation of the present technology and may be includedin more than one implementation. In addition, such phrases do notnecessarily refer to the same embodiments or different embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

The skilled artisan will understand that the drawings, described below,are for illustration purposes only. The drawings are not intended tolimit the scope of the present teachings in any way.

FIG. 1 is a block diagram that illustrates a computer system, upon whichembodiments of the present teachings may be implemented.

FIG. 2 is an exemplary diagram showing components of a GNSS-R system,upon which embodiments of the present teachings may be implemented.

FIG. 3 is an exemplary diagram showing coherent and noncoherentreflections of carrier signals from smooth and rough surfacesrespectively to a receiver, upon which embodiments of the presentteachings may be implemented.

FIG. 4 is an exemplary block diagram of a GNSS-R receiver showing thelocation of IF signal processing, upon which embodiments of the presentteachings may be implemented.

FIG. 5 is an exemplary block diagram showing the IF signal processing ina GNSS-R receiver used to account for low SNR, large signal amplitudefluctuations, and signal frequency shifts due to the Doppler effect,upon which embodiments of the present teachings may be implemented.

FIG. 6 is an exemplary block diagram showing MS-OL carrier trackingprocessing, upon which embodiments of the present teachings may beimplemented.

FIG. 7 is an exemplary plot of the (C/N₀) and the Δϕ of a reflected GNSScarrier signal estimated using MS-OL carrier tracking processing, uponwhich embodiments of the present teachings may be implemented.

FIG. 8 is an exemplary block diagram showing ACL carrier trackingprocessing, upon which embodiments of the present teachings may beimplemented.

FIG. 9 is an exemplary block diagram showing the IF signal processingused to implement AHT processing, in accordance with variousembodiments.

FIG. 10 is an exemplary block diagram showing AHT processing, inaccordance with various embodiments.

FIG. 11 is an exemplary flowchart showing a set of operations forapplying AHT processing using a Kalman filter as an example of theestimator of FIG. 10 , in accordance with various embodiments.

FIG. 12 is an exemplary diagram of a receiver for tracking a C/N₀ and aΔϕ of a reflected RF carrier signal, in accordance with variousembodiments.

FIG. 13 is an exemplary flowchart showing a method for tracking a C/N₀and a Δϕ of a reflected RF carrier signal, in accordance with variousembodiments.

FIG. 14 is a schematic diagram of a system that includes one or moredistinct software modules that perform a method for tracking a C/N₀ anda Δϕ of a reflected RF carrier signal, in accordance with variousembodiments.

FIG. 15 is an exemplary plot showing how AHT processing can improve anRF receiver by improving the tracking of a reflected RF carrier signal,in accordance with various embodiments.

FIG. 16 is an exemplary diagram illustrating sea surface heightretrieval using GNSS-R, in accordance with various embodiments.

The drawings have not necessarily been drawn to scale. Similarly, somecomponents and/or operations may be separated into different blocks orcombined into a single block for the purposes of discussion of some ofthe embodiments of the present technology. Moreover, while thetechnology is amenable to various modifications and alternative forms,specific embodiments have been shown by way of example in the drawingsand are described in detail below. The intention, however, is not tolimit the technology to the particular embodiments described. On thecontrary, the technology is intended to cover all modifications,equivalents, and alternatives falling within the scope of the technologyas defined by the appended claims.

DESCRIPTION OF VARIOUS EMBODIMENTS Computer-Implemented System

FIG. 1 is a block diagram that illustrates a computer system 100, uponwhich embodiments of the present teachings may be implemented. Computersystem 100 includes a bus 102 or other communication mechanism forcommunicating information, and a processor 104 coupled with bus 102 forprocessing information. Computer system 100 also includes a memory 106,which can be a random-access memory (RAM) or other dynamic storagedevice, coupled to bus 102 for storing instructions to be executed byprocessor 104. Memory 106 also may be used for storing temporaryvariables or other intermediate information during execution ofinstructions to be executed by processor 104. Computer system 100further includes a read-only memory (ROM) 108 or other static storagedevice coupled to bus 102 for storing static information andinstructions for processor 104. A storage device 110, such as a magneticdisk or optical disk, is provided and coupled to bus 102 for storinginformation and instructions.

Computer system 100 may be coupled via bus 102 to a display 112, such asa cathode ray tube (CRT) or liquid crystal display (LCD), for displayinginformation to a computer user. An input device 114, includingalphanumeric and other keys, is coupled to bus 102 for communicatinginformation and command selections to processor 104. Another type ofuser input device is cursor control 116, such as a mouse, a trackball orcursor direction keys for communicating direction information andcommand selections to processor 104 and for controlling cursor movementon display 112. This input device typically has two degrees of freedomin two axes, a first axis (i.e., x) and a second axis (i.e., y), thatallows the device to specify positions in a plane.

A computer system 100 can perform the present teachings. Consistent withcertain implementations of the present teachings, results are providedby computer system 100 in response to processor 104 executing one ormore sequences of one or more instructions contained in memory 106. Suchinstructions may be read into memory 106 from another computer-readablemedium, such as storage device 110. Execution of the sequences ofinstructions contained in memory 106 causes processor 104 to perform theprocess described herein. Alternatively, hard-wired circuitry may beused in place of or in combination with software instructions toimplement the present teachings. Thus, implementations of the presentteachings are not limited to any specific combination of hardwarecircuitry and software.

In various embodiments, computer system 100 can be connected to one ormore other computer systems, like computer system 100, across a networkto form a networked system. The network can include a private network ora public network such as the Internet. In the networked system, one ormore computer systems can store and serve the data to other computersystems. The one or more computer systems that store and serve the datacan be referred to as servers or the cloud, in a cloud computingscenario. The one or more computer systems can include one or more webservers, for example. The other computer systems that send and receivedata to and from the servers or the cloud can be referred to as clientor cloud devices, for example.

The terms “computer-readable medium” or “computer program product” asused herein refer to any media that participates in providinginstructions to processor 104 for execution. Such a medium may take manyforms, including but not limited to, non-volatile media, volatile media,and transmission media. Non-volatile media includes, for example,optical or magnetic disks, such as storage device 110. Volatile mediaincludes dynamic memory, such as memory 106. Transmission media includescoaxial cables, copper wire, and fiber optics, including the wires thatcomprise bus 102.

Common forms of computer-readable media or computer program productsinclude, for example, a floppy disk, a flexible disk, hard disk,magnetic tape, or any other magnetic medium, a CD-ROM, digital videodisc (DVD), a Blu-ray Disc, any other optical medium, a thumb drive, amemory card, a RAM, PROM, and EPROM, a FLASH-EPROM, any other memorychip or cartridge, or any other tangible medium from which a computercan read.

Various forms of computer-readable media or computer program productsmay be involved in carrying one or more sequences of one or moreinstructions to processor 104 for execution. For example, theinstructions may initially be carried on the magnetic disk of a remotecomputer. The remote computer can load the instructions into its dynamicmemory and send the instructions over a telephone line using a modem. Amodem local to computer system 100 can receive the data on the telephoneline and use an infra-red transmitter to convert the data to aninfra-red signal. An infra-red detector coupled to bus 102 can receivethe data carried in the infra-red signal and place the data on bus 102.Bus 102 carries the data to memory 106, from which processor 104retrieves and executes the instructions. The instructions received bymemory 106 may optionally be stored on storage device 110 either beforeor after execution by processor 104.

In accordance with various embodiments, instructions configured to beexecuted by a processor to perform a method are stored on acomputer-readable medium. The computer-readable medium can be a devicethat stores digital information. For example, a computer-readable mediumor a computer program product includes a compact disc read-only memory(CD-ROM) as is known in the art for storing software. Thecomputer-readable medium or computer program product is accessed by aprocessor suitable for executing instructions configured to be executed.

The following descriptions of various implementations of the presentteachings have been presented for purposes of illustration anddescription. It is not exhaustive and does not limit the presentteachings to the precise form disclosed. Modifications and variationsare possible in light of the above teachings or may be acquired frompracticing the present teachings. Additionally, the describedimplementation includes software but the present teachings may beimplemented as a combination of hardware and software or in hardwarealone. The present teachings may be implemented with bothobject-oriented and non-object-oriented programming systems.

Carrier Signal Tracking for Topographical Height Estimation

As described above, radio signals reflected from the earth's surface canbe used to derive the properties of the reflection surface. The carrierphase measurement from surface-reflected radio signals enableshigh-precision remote sensing applications, such as sea level and seaice monitoring, terrain topography, snow-water-equivalent (SWE)measurements, etc. However, the carrier phase measurement can only beobtained from coherent reflections. Coherent reflection occurs when thereflection surface is relatively smooth, i.e., if the roughness of thereflection surface is comparable to or larger than the signalwavelength, the reflection is non-coherent. For example, few studieshave shown coherent reflection observations of GNSS signals over openocean from a space-borne platform. This is because the ocean surface isrelatively rough. Only a small amount of coherent signal exists in thereflected signals at low-grazing angles when the ocean surface isrelatively calm. In addition, the reflected signal usually has a low SNRand large signal amplitude fluctuations caused by multipathinterferences, which impose great challenges in the receiver carriersignal processing.

Few technologies have been developed specifically for processing radiosignals of coherent reflections. Most of the current GNSS-R missions andexperiments follow an OL signal tracking technique which was originallyproposed for radio occultation.

In the OL signal tracking technique, the received reflected radio signalis correlated with the reference signal which is generated based on aspecular reflection model. Through specular reflection modeling, therange and range rate of the reflected signal transmission path areestimated based on the transmitter PVT (usually obtained from orbitparameters, such as GNSS almanac and ephemeris) and receiver PVT(usually obtained from a navigation processor). The range and range ratefrom the specular reflection model are converted to code phase andDoppler frequency, based on which the reference signal is generated. Thecarrier phase in the reference signal is the accumulated Dopplerfrequency, in radians, overtime. A carrier phase discriminator isapplied to measure the carrier phase error of the reference signal.Then, the carrier phase-based range measurement is obtained by addingthe unwrapped carrier phase error measurement to the accumulated Dopplerfrequency.

Although the OL signal tracking technique is robust and may besufficient for some circumstances, it lacks accuracy and producesfrequent occurrences of discontinuities (often referred to as carrierphase cycle-slips) in measurements, which is important forhigh-precision remote sensing applications. For reflected radio signalswith only a small amount of coherent component, a low SNR, and severemultipath interferences, OL measurements are especially unreliable.

One OL signal tracking technique, which is described above, is MS-OLprocessing. In MS-OL processing, a carrier signal replica is generatedbased on a Doppler model. The carrier signal replica is then correlatedwith the reflected GNSS signal to provide C/N₀ and Δϕ estimates for thesignal. The MS-OL carrier tracking method is simple to implement and hasexcellent robustness. However, when C/N₀ is low or when the reflectedcarrier signal experiences multipath interferences, the MS-OL trackingresults can be noisy, and the errors produced can accumulate in thecarrier phase observation and cause numerous phase discontinuities.

In order to overcome the noisy tracking results produced by MS-OLcarrier tracking processing, ACL processing was developed. As describedabove, when properly tuned, ACL processing provides improved accuracyand fewer phase discontinuities in carrier phase measurements ascompared to MS-OL processing or the conventional closed-loop PLLprocessing.

The ACL carrier tracking method provides improved results over OLcarrier tracking methods by taking advantage of the characteristics ofsignal dynamics and adaptive filter tuning based on a real-timeestimated C/N₀. However, one problem with using ACL processing forGNSS-R signal tracking is that its performance is dependent on accurateinitialization and tuning. ACL processing can lose lock of the reflectedsignal when there is not a sufficient amount of coherent signal.

In summary, both MS-OL carrier tracking processing and ACL carriertracking have been used to provide C/N₀ and Δϕ estimates for a reflectedcarrier signal, which were then used, in turn, to estimate topologicalsurface heights with a resolution on the order of centimeters. However,when the C/N₀ of the reflected signal was low, MS-OL processing wasfound to produce phase discontinuities and, when the amount of coherentreflected signal was reduced, ACL processing was found to lose lock ofthe reflected signal. As a result, additional systems and methods areneeded to provide signal tracking of reflected carrier signals withoutphase discontinuities and without losing lock of the reflected signals.

In various embodiments, AHT processing is used to provide signaltracking of reflected carrier signals without phase discontinuities andwithout losing lock of the reflected signals. Most generally, AHTprocessing uses both the Doppler model of MS-OL processing and thefeedback loop of ACL processing to develop a replica carrier signal forcorrelation with received reflected carrier signal.

Previously, it was not thought possible or advantageous to combinefeatures of MS-OL processing and ACL processing. For example, MS-OLprocessing's simplicity (due to no feedback loop) and ability to be usedin real-time gave it advantages over ACL processing. Similarly, ACLprocessing's replacement of the Doppler model with feedback fromprevious results provided better Δϕ estimates than MS-OL.

In various embodiments, however, features of MS-OL processing and ACLprocessing are combined. However, AHT processing still differs fromMS-OL processing. Some significant differences between AHT processingand OL processing, in general, are described as follows:

The reference signal in AHT processing is generated using the code phaseand Doppler frequency obtained from the specular reflection model andthe carrier phase obtained from the closed-loop feedback of estimatedsignal parameters.

An estimator is applied to estimate the Doppler frequency and carrierphase of the reflected radio signal. In some embodiments, the presenttechnology adopts a state-space problem formulation based on the signaldynamics modeling, the measurement modeling, and the characterization ofsignal dynamics noise and measurement noise. In some embodiments, theinformation of receiver platform dynamics, the C/N₀ of the receivedsignal, and the properties of the reflection surfaces can be obtainedfrom external sources or real-time estimation and be used to adaptivelyadjust the filter parameters to achieve an optimal filteringperformance.

In some embodiments of the present technology, the DLOS signalprocessing outputs are used to aid the reflected signal processing. Forexample, the estimated signal parameters and the decoded navigation databits of the DLOS signal are used to model the signal parameters and wipeoff the data bits of the reflected signal.

In the following description, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of embodiments of the present technology. It will beapparent, however, to one skilled in the art that embodiments of thepresent technology may be practiced without some of these specificdetails. While, for convenience, embodiments of the present technologyare described with reference to a space-borne GNSS-R environment toaccurately show an implementation of the technology in a GNSS-Rreceiver, other embodiments of the present technology are equallyapplicable to various other applications. The scope of the presenttechnology is intended to cover all such embodiments that may fallwithin the scope of the appended claims, either literally or under thedoctrine of equivalents. For example, the radio signal transmitted froma communication satellite and the radio signal received on an airborneplatform can also be processed by the technology disclosed.

As described above, FIG. 4 shows the location of IF signal processing aGNSS-R receiver. FIG. 5 shows generically the type of IF signalprocessing performed in a GNSS-R receiver in order to account for lowsignal SNR, large signal amplitude fluctuations, and signal frequencyshifts due to the Doppler effect.

FIG. 9 is an exemplary block diagram 900 showing the IF signalprocessing used to implement AHT processing, in accordance with variousembodiments. The IF signal processing of FIG. 9 takes place in IF signalprocessing system 430 of the GNSS-R receiver of FIG. 4 , for example.

FIG. 9 includes DLOS IF signal processing module 910, reflected IFsignal processing module 911, and specular reflection modeling module912. The input to DLOS IF signal processing module 910 includes the DLOSIF signal 901. The input to reflected IF signal processing module 911includes reflected IF signal 902. The input to specular reflectionmodeling module 912 is parameters 903, including, but not limited to, aGeoid model or a mean sea surface (MSS) model.

DLOS IF signal processing module 910 includes navigation processing,which includes signal acquisition, signal tracking, and providing anavigation solution. The output of the DLOS IF signal processing system910 includes estimated PVT parameters 910 a of the receiver platform,GNSS satellite orbit parameters 910 b, signal parameters of the DLOSsignal 910 c, and decoded navigation data bits 910 d.

Specular reflection modeling module 912 calculates GNSS satellite PVT912 c, the SP location 912 d, the range difference 912 a between theDLOS signal and the reflected signal, and the range rate difference 912b between the DLOS signal and the reflected signal.

Reflected IF signal processing system 911 implements AHT processing toestimate the signal parameters and the C/N₀ of the reflected radiosignal. The input to reflected IF signal processing system 911 includesestimated signal parameters of the DLOS signal 910 c, decoded navigationdata bits 910 d, range difference 912 a between the DLOS signal and thereflected signal, and range rate difference 912 b between the DLOSsignal and the reflected signal. The output of reflected IF signalprocessing system 911 is estimated signal parameters 911 a of thereflected signal.

Phase range retrieval module 920 retrieves carrier phase-based rangemeasurements 920 a from the estimated signal parameters 911 a of thereflected signal. Phase range retrieval module 920 includes theconversion from a radio signal carrier phase to a range (not shown),cycle-slips detection and correction (not shown), and a smoother for thephase range measurements (not shown).

Sea surface height 940 is retrieved from height retrieval module 930using carrier phase-based range measurements 920 a, GNSS satellite PVT912 c, the (SP) location 912 d, the range difference 912 a between theDLOS signal and the reflected signal, and the mean sea surface model903.

FIG. 16 is an exemplary diagram 1600 illustrating sea surface heightretrieval using GNSS-R, in accordance with various embodiments. As shownin FIG. 16 , the sea surface height 940 of FIG. 9 is retrieved byestimating the altitude of SP 1650. Based on the location of the GNSSsatellite 1610 when the signal is transmitted, the location of the LEOsatellite 1620 when the signal is received, and the mean sea surfacemodel 903 of FIG. 9 , the location of SP 1660 can be predicted, and thetotal range of the reflected signal transmission paths 1640 a and 1640 bcan be predicted and denoted as RPred. The total carrier phase-basedrange of the reflected signal transmission paths 1630 a and 1630 b ismeasured through reflected GNSS signal processing as 920 a of FIG. 9 anddenoted as RMeas. The measured altitude error ΔH 1680 of the predictedSP 1660 is obtained as

${{\Delta H} = \frac{R_{Meas} - R_{Pred}}{2{\cos(\theta)}}},$

where θ is the elevation angle 1670 at SP 1660. Then, the altitude of SP1650 is estimated by correcting the altitude of predicted SP 1660 usingthe measured altitude error 1680, so that the sea surface height 940 ofFIG. 9 is retrieved.

Adaptive Hybrid Carrier Tracking

FIG. 10 is an exemplary block diagram 1000 showing AHT processing, inaccordance with various embodiments. As shown in FIG. 10 , AHTprocessing is performed using signal parameter modeling module 1020,reference generator 1010, correlator 1030, discriminator 1040, estimator1050, and C/N₀ estimator 1060.

Using the inputs of the estimated signal parameters of the DLOS signal910 c, the range difference 912 a between the DLOS signal and thereflected signal, and the range rate difference 912 b between the DLOSsignal and the reflected signal, signal parameter modeling module 1020generates the modeled signal parameters 1020 a, i.e., code phase andDoppler frequency, which are inputs to reference generator 1010. Otherinputs to reference generator 1010 include decoded navigation data bits910 d and the feedback of estimated carrier phase 1070. Referencegenerator 1010 generates reference signals 1010 a with in-phase (I) andquadrature-phase (Q) carriers, respectively, and with navigation databits modulated in it. If the received GNSS signals are not in thebaseband, i.e., IF #0 (Hz), the reference signals are generated with theIF carrier component in it, which means the carrier frequency is equalto the summation of the Doppler frequency and the IF.

Correlator 1030 correlates input reflected IF signal 1030 with thereference signals 1010 a to obtain correlation results 1030 a, i.e., Iand Q. C/N₀ estimator 1060 and discriminator 1040 utilize correlationresults 1030 a to estimate C/N₀ 1060 a and carrier phase errormeasurement 1040 a (Δϕ), respectively.

Estimator 1050 is controlled by the C/N₀ 1060 a from C/N₀ estimator 1060to adjust the filter parameters to eliminate the noise in carrier phasemeasurement 1040 a. Empirical phase noise model 1080 can also beincorporated into estimator 1050. The outputs of estimator 1050 includecarrier phase estimation 1070 and the Doppler frequency estimation 1090.

Adaptive Hybrid Tracking Operations

FIG. 11 is an exemplary flowchart showing a set of operations forapplying AHT processing using a Kalman filter as an example of estimator1050 of FIG. 10 , in accordance with various embodiments. Estimator 1050of FIG. 10 is not limited to a Kalman filter and can be, but is notlimited to, a proportional integral filter or a Weiner filter.

Let x_(i,k+1)=[φ_(i) ω_(i)]_(k+1) ^(T) represent the i^(th) carrierstate at the k+1^(th) epoch, where i=1, 2 represent GPS L1 and L2signals, φ_(i) and ω_(i) represent the carrier phase (rad) and Dopplerfrequency (rad/s). Let δφ_(i,k) represent the carrier phase errormeasurement 1040 a of the i^(ih) carrier at the k^(th) epoch. Estimator1050, e.g., the Kalman filter, estimates the carrier state based on theprevious state estimation {circumflex over (x)}_(i,k) and the carrierphase error measurement δφ_(i,k+1):

{circumflex over (x)} _(i,k+1) =A{circumflex over (x)} _(i,k)+A{circumflex over (x)} _(i,k) +AL _(i,k+1)δφ_(i,k+1)  (1)

where A is the transition matrix and has the following form:

$\begin{matrix}{{A = \begin{bmatrix}1 & T \\0 & 1\end{bmatrix}},} & (2)\end{matrix}$

L_(i,k+1) is the 2×1 dimensional Kalman gain controlled by the estimatedsignal C/N₀ 1060 a.

The following description illustrates in greater detail the operationsof various embodiments.

Returning to FIG. 11 , in step 1110, the state vector x_(i,k) and thecovariance matrix of the Kalman filter are initialized. Three separatesteps follow step 1110: the local reference signals are generated instep 1120 based on the state vector x_(i,k) and the code phase fromsignal parameter modeling module 1020 of FIG. 10 , the reference signalsare correlated with the received signals in step 1130, and the carrierdiscriminator determines carrier error measurements and the C/N₀estimator determines the signal C/N₀, both using the correlationoutputs, in step 1140. Following step 1140, the Kalman gain isdetermined based on the estimated signal C/N₀ in step 1150. Next, instep 1160, an estimation of the state vector is determined by the Kalmanfilter as described in Equation (1). The state vector for the next epochis predicted based on the state dynamics model in step 1170. Then, instep 1180, the Doppler frequency ω_(i) in the predicted state vector isreset based on signal parameter modeling module 1020 of FIG. 10 and,meanwhile, the variance of Doppler frequency in the predicted statecovariance matrix is reset as well. Each step 1180 leads back to step1120, reinitializing the process.

Receiver for Tracking C/N₀ and Δϕ of a Reflected Carrier Signal

FIG. 12 is an exemplary diagram 1200 of a receiver for tracking a C/N₀and a Δϕ of a reflected RF carrier signal, in accordance with variousembodiments. Receiver 1210 includes one or more antennas 1211, RFfront-end circuitry 1212, ADC 1213, and processor 1214.

One or more antennas 1211 receive DLOS RF signal component 1221 and RFsignal component 1222 of RF carrier signal 1225. RF signal component1222 is reflected from point 1230 on surface 1240 of earth 1250. RFcarrier signal 1225 is transmitted from transmitter 1220 located abovesurface 1240 of earth 1250.

RF front-end circuitry 1212 down-converts DLOS RF signal component 1221to DLOS IF signal 1261. RF front-end circuitry 1212 also down-convertsRF signal component 1222 that is reflected from point 1230 to reflectedIF signal 1262.

ADC 1213 converts DLOS IF signal 1261 to digital DLOS IF signal 1271.ADC 1213 also converts reflected IF signal 1262 to digital reflected IFsignal 1272.

Processor 1214 is used to receive signals, process signals, producedata, or provide control instructions. Processor 1214 can be part ofreceiver 1210, as shown in FIG. 12 , or can be a separate device, forexample. Processor 1214 can be, but is not limited to, a controller, acomputer, a microprocessor, the computer system of FIG. 1 , or anydevice capable of sending, receiving, and processing signals and data.

Processor 1214 generates modeled reference signal parameters usingdigital DLOS IF signal 1271 and known locations of one or more antennas1211, transmitter 1220, and point 1230. Processor 1214 generates areference signal based on the modeled reference signal parameters andfeedback of a previously estimated Δϕ. Processor 1214 correlates thereference signal with digital reflected IF signal 1272 to producein-phase (I) and quadrature-phase (Q) correlation results. Processor1214 calculates an estimated C/N₀ and an estimated Δϕ for digitalreflected IF signal 1272 from the correlation results.

In various embodiments, one or more antennas 1211 can include a firstantenna to receive DLOS RF signal component 1221 and a second antenna toreceive RF signal component 1222 that is reflected from point 1230, asshown in FIG. 12 .

In various embodiments, processor 1214 further calculates a centimetricheight at point 1230 from the estimated Δϕ.

In various embodiments, RF carrier signal 1225 is a GNSS carrier signaland the locations of one or more antennas 1211, transmitter 1220, andpoint 1230 are determined from information carried by the GNSS carriersignal.

In various embodiments, RF carrier signal 1225 is a carrier signal of acommunications system and the locations of the one or more antennas, thetransmitter, and the point are determined from information transmittedseparately from ground stations of the communications system.

In various embodiments, the feedback of a previously estimated Δϕ is astate vector and the reference signal is generated based on the modeledreference signal parameters and the state vector. The state vector isestimated using a filter, for example. The filter can be, but is notlimited to, a Kalman filter, a proportional integral filter, or a Weinerfilter.

In various embodiments, processor 1214 further eliminates noise in theestimated Δϕ by adjusting parameters of the filter based on theestimated C/N₀ and the estimated Δϕ. Processor 1214 can also adjustparameters of the filter based on an empirical phase noise model.

In various embodiments, processor 1214 calculates the estimated C/N₀ andthe estimated Δϕ in real-time.

Method for Tracking C/N₀ and Δϕ of a Reflected Carrier Signal

FIG. 13 is an exemplary flowchart 1300 showing a method for tracking aC/N₀ and a Δϕ of a reflected RF carrier signal, in accordance withvarious embodiments.

In step 1310 of method 1300, a DLOS RF signal component and a reflectedRF signal component of an RF carrier signal are received using one ormore antennas. The reflected RF signal component is reflected from apoint on the surface of the earth. The RF carrier signal is transmittedfrom a transmitter located above the surface of the earth.

In step 1320, the DLOS RF signal component is down-converted to a DLOSIF signal using RF front-end circuitry. The RF signal component that isreflected from the point is down-converted to a reflected IF signal alsousing the RF front-end circuitry.

In step 1330, the DLOS IF signal is converted to a digital DLOS IFsignal and the reflected IF signal is converted to a digital reflectedIF signal using an ADC.

In step 1340, modeled reference signal parameters are generated usingthe digital DLOS IF signal and known locations of the one or moreantennas, the transmitter, and the point using a processor.

In step 1350, a reference signal is generated based on the modeledreference signal parameters and feedback of a previously estimated Δϕusing the processor.

In step 1360, the reference signal is correlated with the digitalreflected IF signal to produce in-phase (I) and quadrature-phase (Q)correlation results using the processor.

In step 1370, an estimated C/N₀ and an estimated Δϕ are calculated forthe digital reflected IF signal from the correlation results using theprocessor.

Computer Program Product for Tracking C/N₀ and Δϕ of a Reflected CarrierSignal

In various embodiments, computer program products include a tangiblecomputer-readable storage medium whose contents include a program withinstructions being executed on a processor so as to perform a method fortracking C/N₀ and Δϕ of a reflected RF carrier signal. This method isperformed by a system that includes one or more distinct softwaremodules.

FIG. 14 is a schematic diagram of a system 1400 that includes one ormore distinct software modules that perform a method for tracking C/N₀and Δϕ of a reflected RF carrier signal, in accordance with variousembodiments. System 1400 includes signal parameter modeling module 1410,reference generator 1420, correlator 1430, and estimator 1440.

Signal parameter modeling module 1410 generates modeled reference signalparameters using a DLOS IF signal and known locations of one or moreantennas, a transmitter located above the surface of the earth, and apoint on the surface of the earth. A DLOS RF signal component and areflected RF signal component of an RF carrier signal are received usingthe one or more antennas. The reflected RF signal component is reflectedfrom the point. The RF carrier signal is transmitted from thetransmitter. The DLOS RF signal component is down-converted to a DLOS IFsignal using RF front-end circuitry. The reflected RF signal componentis down-converted to a reflected IF signal also using the RF front-endcircuitry. The DLOS IF signal is converted to the digital DLOS IF signaland the reflected IF signal is converted to a digital reflected IFsignal using an ADC.

Reference generator 1420 generates a reference signal based on themodeled reference signal parameters and feedback of a previouslyestimated Δϕ.

Correlator 1430 correlates the reference signal with the digitalreflected IF signal to produce in-phase (I) and quadrature-phase (Q)correlation results.

Estimator 1440 calculates an estimated C/N₀ and an estimated Δϕ for thedigital reflected IF signal from the correlation results.

Adaptive Hybrid Tracking Improves an RF Receiver

FIG. 15 is an exemplary plot 1500 showing how AHT processing can improvean RF receiver by improving the tracking of a reflected RF carriersignal, in accordance with various embodiments. In plot 1500, estimatedΔϕ data values for MS-OL 1501, ACL 1502, and AHT 1503 processing areplotted as a function of time. The time values represent differentspecular points on the surface of the earth from which a reflectedcomponent of the RF carrier signal was analyzed.

Plot 1500, shows that the estimated Δϕ data values from MS-OL processing1501 include many phase discontinuities and large noise, while the Δϕdata values from ACL processing 1502 and AHT processing 1503 do notinclude any phase discontinuity and have less noise than those fromMS-OL processing. As mentioned above, ACL processing is impractical foronboard operation in real-time. As a result, AHT processing, as apractical approach for real-time operation, improves an RF receiver byproviding signal tracking of reflected carrier signals with fewer phasediscontinuities and less noise than the traditional MS-OL processing.

Unless the context clearly requires otherwise, throughout thedescription and the claims, the words “comprise,” “comprising,” and thelike are to be construed in an inclusive sense, as opposed to anexclusive or exhaustive sense; that is to say, in the sense of“including, but not limited to.” As used herein, the terms “connected,”“coupled,” or any variant thereof means any connection or coupling,either direct or indirect, between two or more elements; the coupling orconnection between the elements can be physical, logical, or acombination thereof. Additionally, the words “herein,” “above,” “below,”and words of similar import, when used in this application, refer tothis application as a whole and not to any particular portions of thisapplication. Where the context permits, words in the above DetailedDescription using the singular or plural number may also include theplural or singular number respectively. The word “or,” in reference to alist of two or more items, covers all of the following interpretationsof the word: any of the items in the list, all of the items in the list,and any combination of the items in the list.

The above Detailed Description of examples of the technology is notintended to be exhaustive or to limit the technology to the precise formdisclosed above. While specific examples for the technology aredescribed above for illustrative purposes, various equivalentmodifications are possible within the scope of the technology, as thoseskilled in the relevant art will recognize. For example, while processesor blocks are presented in a given order, alternative implementationsmay perform routines having steps, or employ systems having blocks, in adifferent order, and some processes or blocks may be deleted, moved,added, subdivided, combined, and/or modified to provide alternative orsub-combinations. Each of these processes or blocks may be implementedin a variety of different ways. Also, while processes or blocks are attimes shown as being performed in series, these processes or blocks mayinstead be performed or implemented in parallel, or may be performed atdifferent times. Further any specific numbers noted herein are onlyexamples: alternative implementations may employ differing values orranges.

The teachings of the technology provided herein can be applied to othersystems, not necessarily the system described above. The elements andacts of the various examples described above can be combined to providefurther implementations of the technology. Some alternativeimplementations of the technology may include not only additionalelements to those implementations noted above, but also may includefewer elements.

These and other changes can be made to the technology in light of theabove Detailed Description. While the above description describescertain examples of the technology, and describes the best modecontemplated, no matter how detailed the above appears in text, thetechnology can be practiced in many ways. Details of the system may varyconsiderably in its specific implementation, while still beingencompassed by the technology disclosed herein. As noted above,particular terminology used when describing certain features or aspectsof the technology should not be taken to imply that the terminology isbeing redefined herein to be restricted to any specific characteristics,features, or aspects of the technology with which that terminology isassociated. In general, the terms used in the following claims shouldnot be construed to limit the technology to the specific examplesdisclosed in the specification, unless the above Detailed Descriptionsection explicitly defines such terms. Accordingly, the actual scope ofthe technology encompasses not only the disclosed examples, but also allequivalent ways of practicing or implementing the technology under theclaims.

To reduce the number of claims, certain aspects of the technology arepresented below in certain claim forms, but the applicant contemplatesthe various aspects of the technology in any number of claim forms. Forexample, while only one aspect of the technology is recited as acomputer-readable medium claim, other aspects may likewise be embodiedas a computer-readable medium claim, or in other forms, such as beingembodied in a means-plus-function claim. Any claims intended to betreated under 35 U.S.C. § 112(f) will begin with the words “means for,”but use of the term “for” in any other context is not intended to invoketreatment under 35 U.S.C. § 112(f). Accordingly, the applicant reservesthe right to pursue additional claims after filing this application topursue such additional claim forms, in either this application or in acontinuing application.

What is claimed is:
 1. A system for tracking a carrier-to-noise ratio(C/N₀) and a phase correction (Δϕ) of a reflected radio frequency (RF)carrier signal, comprising: one or more processors that receive adigital direct line-of-sight (DLOS) intermediate frequency (IF) signalof a DLOS component of an RF carrier signal transmitted by a transmitterlocated above the surface of the earth and a digital reflected IF signalof a reflected component of the carrier signal that is reflected from aspecular point (SP) on the surface of the earth, generate modeledreference signal parameters using the digital DLOS IF signal and knownlocations of one or more receiving antennas, the transmitter, and theSP, generate a reference signal based on the modeled reference signalparameters and feedback of a previously estimated Δϕ, correlate thereference signal with the digital reflected IF signal to producein-phase (I) and quadrature-phase (Q) correlation results, and calculatean estimated C/N₀ and an estimated Δϕ for the digital reflected IFsignal from the correlation results.
 2. The system of claim 1, whereinthe one or more receiving antennas comprise a first antenna to receivethe DLOS component and a second antenna to receive the reflectedcomponent.
 3. The system of claim 1, wherein the one or more processorsfurther calculate a centimetric height at the SP from the estimated Δϕ.4. The system of claim 1, wherein the carrier signal comprises a globalnavigation satellite system (GNSS) carrier signal and the locations ofthe one or more receiving antennas, the transmitter, and the SP aredetermined from information carried by the GNSS carrier signal.
 5. Thesystem of claim 1, wherein the carrier signal comprises a carrier signalof a communications system and the locations of the one or morereceiving antennas, the transmitter, and the SP are determined frominformation transmitted separately from ground stations of thecommunications system.
 6. The system of claim 1, wherein the feedback ofa previously estimated Δϕ comprises a state vector and the referencesignal is generated based on the modeled reference signal parameters andthe state vector.
 7. The system of claim 6, wherein the state vector isestimated using a filter.
 8. The system of claim 7, wherein the filtercomprises a Kalman filter.
 9. The system of claim 7, wherein the filtercomprises a proportional integral filter.
 10. The system of claim 7,wherein the filter comprises a Weiner filter.
 11. The system of claim 8,wherein the one or more processors further eliminate noise in theestimated Δϕ by adjusting parameters of the filter based on theestimated C/N₀ and the estimated Δϕ.
 12. The system of claim 11, whereinthe one or more processors further adjust the parameters of the filterbased on an empirical phase noise model.
 13. The system of claim 1,wherein the one or more processors calculate the estimated C/N₀ and theestimated Δϕ in real-time.
 14. A method for tracking carrier-to-noiseratio (C/N₀) and a phase correction (Δϕ) of a reflected radio frequency(RF) carrier signal, comprising: receiving a digital directline-of-sight (DLOS) intermediate frequency (IF) signal of a DLOScomponent of an RF carrier signal transmitted by a transmitter locatedabove the surface of the earth and a digital reflected IF signal of areflected component of the carrier signal that is reflected from aspecular point (SP) on the surface of the earth; generating modeledreference signal parameters using the digital DLOS IF signal and knownlocations of one or more receiving antennas, the transmitter, and theSP; generating a reference signal based on the modeled reference signalparameters and feedback of a previously estimated Δϕ; correlating thereference signal with the digital reflected IF signal to producein-phase (I) and quadrature-phase (Q) correlation results; andcalculating an estimated C/N₀ and an estimated Δϕ for the digitalreflected IF signal from the correlation results.
 15. The method ofclaim 14, wherein the one or more receiving antennas comprise a firstantenna to receive the DLOS component and a second antenna to receivethe reflected component.
 16. The method of claim 14, further comprisingcalculating a centimetric height at the SP from the estimated Δϕ. 17.The method of claim 14, wherein the carrier signal comprises a globalnavigation satellite system (GNSS) carrier signal and the locations ofthe one or more receiving antennas, the transmitter, and the SP aredetermined from information carried by the GNSS carrier signal.
 18. Themethod of claim 14, wherein the carrier signal comprises a carriersignal of a communications system and the locations of the one or morereceiving antennas, the transmitter, and the SP are determined frominformation transmitted separately from ground stations of thecommunications system.
 19. The method of claim 14, wherein the feedbackof a previously estimated Δϕ comprises a state vector and the referencesignal is generated based on the modeled reference signal parameters andthe state vector.
 20. A computer program product, comprising anon-transitory and tangible computer-readable storage medium whosecontents include a program with instructions being executed on aprocessor to perform a method for tracking a carrier-to-noise ratio(C/N₀) and a phase correction (Δϕ) of a reflected radio frequency (RF)carrier signal, the method comprising: providing a system, wherein thesystem comprises one or more distinct software modules, and wherein thedistinct software modules comprise a signal parameter modeling module, areference generator, a correlator, and an estimator; receiving a digitaldirect line-of-sight (DLOS) intermediate frequency (IF) signal of a DLOScomponent of an RF carrier signal transmitted by a transmitter locatedabove the surface of the earth and a digital reflected IF signal of areflected component of the carrier signal that is reflected from aspecular point (SP) on the surface of the earth using the signalparameter modeling module; generating modeled reference signalparameters using the digital DLOS IF signal and known locations of oneor more receiving antennas, the transmitter, and the SP using the signalparameter modeling module; generating a reference signal based on themodeled reference signal parameters and feedback of a previouslyestimated Δϕ using the reference generator; correlating the referencesignal with the digital reflected IF signal to produce in-phase (I) andquadrature-phase (Q) correlation results using the correlator; andcalculating an estimated C/N₀ and an estimated Δϕ for the digitalreflected IF signal from the correlation results using the estimator.